To provide for efficient and high quality delivery of information and technology services, it is necessary to be able to track past performance of a system or network and be able to forecast future performance of the system. Current data or real time data is required to monitor the current health or operation of the system or network, whilst past data, or statistical/historical data may be used in, for example, business intelligence (“BI”) applications which process the stored historical data to perform analysis and research on metrics to try and extract the factors relating to past operation and output and to improve future decisions based on the results of the analysis. Future data or forecast data is used to predict future requirements and to support decisions based on identifying trends or other data interactions.
The collected data can fall into two different categories: events and metrics, and are collected from infrastructure management products, such as HP OpenView Operations, HP Network Node Manager, HP OpenView TeMIP, HP OpenView Performance Manager, Mercury SiteScope, or BMC Patrol. An example of an event is of a failure in a system or a system resource being unavailable for some reason, for example an interface on a server being down, or a disk partition being full on a server. A metric is a measure of to what extent a system resource is being used or is available, for example the percentage of CPU consumption or memory use on a given server.
The three functions of monitoring current data, processing past data and generating forecasts are generally provided by separate applications. Accordingly, past data or historical data are stored in a data “warehouse” for example by an ETL process (“Extract, Transform, and Load”) which receives the data, transforms it in accordance with the requirements of the BI system, and loads it into the database. To provide real time monitoring of current data, it is known to provide “dashboard” applications which use particular metrics or indicators to provide appropriate displays to summarize the current status of a system and provide warnings, alerts and current status information. Finally, forecasting relies on appropriate analysis programmes which draw extrapolations from past data and trends by use of appropriate algorithms or models.
Such data analysis may be particularly useful in driving management of information technology infrastructure, such as a network, where there may be specific service level management criteria agreed as part of a service level agreement (“SLA”) with the users of the system. Accordingly, it is desirable to be able to ensure that the SLA is being met, and to identify any future requirements or potential problems. This can be difficult for a system operator as the past data, current information, and forecast data are handled separately and through different applications.